应用气象学报
應用氣象學報
응용기상학보
QUARTERLY JOURNAL OF APPLIED METEOROLOGY
2014年
6期
654-668
,共15页
GNSS掩星%反演资料%资料同化%GRAPES Meso
GNSS掩星%反縯資料%資料同化%GRAPES Meso
GNSS엄성%반연자료%자료동화%GRAPES Meso
GNSS radio occultation%retrieved data%data assimilation%GRAPES Meso
为了进一步提高GRAPES Meso的分析和预报效果，该文在GRAPES Meso三维变分同化系统中建立了同化GNSS／RO反演的大气资料的观测算子，实现了对GNSS／RO 反演的大气资料的同化应用，并通过2013年7月1个月的同化和预报试验分析了GNSS／RO反演大气资料对 GRAPES Meso 模式系统分析和预报的影响。结果表明：增加了GNSS／RO反演大气资料的同化后，GRAPES Meso位势高度场的分析误差明显减小，平均分析误差减小约8％，预报误差略有减小，平均预报误差减小约1％；湿度场的分析误差和预报误差变化不明显，常规观测资料稀少的青藏高原地区的降水预报技巧有所提高，小雨到大雨的ETS（equitable threat score）评分提高约0．01，对全国及其他分区的降水预报技巧总体上有正效果。
為瞭進一步提高GRAPES Meso的分析和預報效果，該文在GRAPES Meso三維變分同化繫統中建立瞭同化GNSS／RO反縯的大氣資料的觀測算子，實現瞭對GNSS／RO 反縯的大氣資料的同化應用，併通過2013年7月1箇月的同化和預報試驗分析瞭GNSS／RO反縯大氣資料對 GRAPES Meso 模式繫統分析和預報的影響。結果錶明：增加瞭GNSS／RO反縯大氣資料的同化後，GRAPES Meso位勢高度場的分析誤差明顯減小，平均分析誤差減小約8％，預報誤差略有減小，平均預報誤差減小約1％；濕度場的分析誤差和預報誤差變化不明顯，常規觀測資料稀少的青藏高原地區的降水預報技巧有所提高，小雨到大雨的ETS（equitable threat score）評分提高約0．01，對全國及其他分區的降水預報技巧總體上有正效果。
위료진일보제고GRAPES Meso적분석화예보효과，해문재GRAPES Meso삼유변분동화계통중건립료동화GNSS／RO반연적대기자료적관측산자，실현료대GNSS／RO 반연적대기자료적동화응용，병통과2013년7월1개월적동화화예보시험분석료GNSS／RO반연대기자료대 GRAPES Meso 모식계통분석화예보적영향。결과표명：증가료GNSS／RO반연대기자료적동화후，GRAPES Meso위세고도장적분석오차명현감소，평균분석오차감소약8％，예보오차략유감소，평균예보오차감소약1％；습도장적분석오차화예보오차변화불명현，상규관측자료희소적청장고원지구적강수예보기교유소제고，소우도대우적ETS（equitable threat score）평분제고약0．01，대전국급기타분구적강수예보기교총체상유정효과。
Radio occultation (RO)observations using the Global Navigation Satellite System (GNSS)provides valuable data to support operational numerical weather prediction,and it is proved that the assimilation of RO data has the potential to significantly improve the accuracy of global and regional meteorological analy-sis and weather prediction.RO observations have many advantages such as high precision,global coverage and high vertical resolution compared with other observations.RO observations provide phase (Level 1a), bending angle (Level 1b),refractivity (Level 2a),retrieved pressure,temperature and humidity profiles (Level 2b),all of which can be assimilated into numerical model.Bending angle and refractivity are proved better choices for assimilation as observation operators are less complicated,and have no disadvantages as-sociated with the modeling of ionospheric effects in the assimilation model.However,assimilation of water vapor,temperature or pressure derived from RO observations have advantages that data forms are same as model variables,and it is proved that assimilation of retrieved data also improve the accuracy of global ana-lyses and forecasts significantly. <br> In the operational GRAPES (Global/Regional Assimilation and Prediction System ) regional (GRAPES Meso)3-dimensional variational (3DVar)system,the analysis is performed in model vertical level,but it can only assimilate the upper-level wind,pressure and humidity from radiosonde report (TEMP),upper-level wind and humidity by AIREP,cloud drift wind (SATOB),the pressure from sur-face station report over land (SYNOP)and over sea,integrated column precipitable water vapor (IPW)re-trieved by ground-based GPS observations and radar wind profiles.In order to assimilate RO retrieved at-mosphere data and address their impacts on analyses and forecasts,observation operators of retrieved hu-midity and pressur eassimilation are developed first,and then quality control and vertical thinning scheme are formed and discussed.Results of one month experiments show that the assimilation of GNSS/RO re-trieved pressure and humidity data have considerable positive impacts on analyses of geopotential height, minor positive impacts on humidity analyses,geopotential height,humidity forecasts,rainfall forecasts, and major positive impacts on rainfall forecast for Qinghai-Tibet region.
